Accurate classification of eye state is a prerequisite for preventing automobile accidents due to driver drowsiness. Previous methods of classification, based on features extracted for a single eye, are vulnerable to eye localization errors and visual obstructions, and most use a fixed threshold for classification, irrespective of variations in the driver’s eye shape and texture. To address the...

Every year 15,000 people are killed on US highways in single vehicle roadway departure automobile crashes, often because of driver drowsiness or inattention. This talk will describe techniques we are developing to prevent these tragedies. Learning is central to this work due to the extreme variability of environmental conditions and individual driver styles. I will describe our recent progress ...

Based on vision sensing and dedicated short range communication (DSRC) disseminating car’s GPS information via v2v communication, a fast collision warning response to an imminent crash has been successfully developed. An embedded dual-platform, DaVinci+XScale-NAV270 was employed to achieve line-marking identification, neighboring vehicles detection, and headway measurement. In order to tackle t...

Each year, many people pass away in car accidents. Drunk driving, distracted and fatigued driving are the leading causes of Some studies have noted that features relevant to drunk driver’s alcohol consumption, smoking, carbon monoxide (CO) concentration car. Hence, it is important necessary detect these factors during avoid driver drowsiness prevent collisions. In this paper, we develop an IoT-...

The proposed system aims to enhance transportation safety by reducing the number of accidents caused driver fatigue and drowsiness, which have become increasingly common. analyzes facial bodily gestures such as eye tiredness yawning identify signs drowsiness fatigue. Eye aspect ratio (EAR) is used detect measuring distances between horizontal vertical landmarks. Yawn detection performed calcula...

background: this study compared the sleep quality and sleepiness in day workers and shift workers. sleep quality and sleepiness in staff nurses were significantly different than employees . shift work is an important factor influencing the sleep quality and sleepiness of nurses. the aim of the present research was to compare three groups: (1) nurses with shiftwork; (2) nurses without shiftwork ...

PURPOSE To identify and appraise the published studies assessing interventions accounting for reducing fatigue and sleepiness while driving. METHODS This systematic review searched the following electronic databases: Medline, Science direct, Scopus, EMBASE, PsycINFO, Transport Database, Cochrane, BIOSIS, ISI Web of Knowledge, specialist road injuries journals and the Australian Transport and ...